CN103616036B  A kind of airborne sensor systematic error estimation based on cooperative target and compensation method  Google Patents
A kind of airborne sensor systematic error estimation based on cooperative target and compensation method Download PDFInfo
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 CN103616036B CN103616036B CN201310630077.2A CN201310630077A CN103616036B CN 103616036 B CN103616036 B CN 103616036B CN 201310630077 A CN201310630077 A CN 201310630077A CN 103616036 B CN103616036 B CN 103616036B
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 G—PHYSICS
 G01—MEASURING; TESTING
 G01S—RADIO DIRECTIONFINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCEDETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
 G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
 G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
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Abstract
Description
Technical field
Inventive algorithm relates to Data fusion technique, particularly to sensor space registration technique, Specifically refer to a kind of airborne sensor systematic error estimation based on cooperative target and compensation method.
Background technology
Modern war is faced with complication, diversified external environment condition, and singlesensor is difficult to Meet the demand that battle field information is analyzed.Increasing it was verified that use multisensor syste Select suitable algorithm that multisource information is carried out fusion treatment, it is possible to obtain than singlesensor more The useful information of horn of plenty.Compared to Method for Single Sensor System, multisensor syste enhances system Survival ability, extend time covering domain and space covering domain, improve the credibility of information. But, vital premise is that these advantages produce accurately solves to go out in fusion process Existing a series of key issues.Spatial registration is one of them key issue, and complete space is joined QuasiResolving probiems comprises the intension of two aspects: registration error estimation and system deviation compensate.Mesh Front space registration problems mainstream research concentrates on the former, and the research to the latter is then mainly reflected in work Journey should be considered by the actual of used time.
Mainly have than more typical systematic error estimation method: realtime quality control methods, a young waiter in a wineshop or an inn Multiplication, maximum likelihood method, Kalman filtering method etc..Realtime quality control methods is to each sensor Measured metric data is averaging processing, and the observation as sensor of averaging is entered And estimating system deviation.This method ignores sensor measurement noise and each sensor relative to public affairs The deviation of the coordinate system impact on registration error altogether, it is adaptable to the situation that measurement noise is less.? Registration problems is converted into leastsquares parameter estimation problem by little square law, by deviation equation Structure and solving of overdetermined systems obtain straggling parameter estimation under least square meaning.This The method of kind is applicable to the registration error estimation of offline mode, because the structure of overdetermined systems needs The sensor metric data in multiple moment.Maximum likelihood method utilizes sensor in System planes Measured value, uses maximum likelihood method to estimate position and the system deviation of target simultaneously, It has used two step recursive optimization methods to accelerate the convergence rate estimated.Kalman filter method is recognized For constant and unrelated with noise during system deviation vector, by structural regime equation and measurement side Journey realizes the estimation of system deviation.Certainly, researcher is also developed other system deviation and is estimated Meter method, or the impact improving or adding some factor of said method.But these The basic ideas of method are consistent: first instrument error equation；Secondly analytical error source, Linearized stability equation；Last according to Parameter Estimation Problem solving system deviation.
Make a general survey of abovementioned canonical system error estimation it appeared that But most of algorithms can only measure Data random error is less even without just effective during random error, this more exacting terms It is implacable in practice.Have ignored partially it addition, more important point is said method The consideration of difference estimation observability, the especially registration error estimation under mobile platform, now Deviation variables not only contains sensor Measurement Biases and also includes platform self navigation deviation, system Observability problem become especially prominent.
System deviation compensates and is primarily referred to as the apriority of deviation profile in sensor detection spatial domain Assuming that.One is to think that deviation is invariable, is evenly distributed in detection spatial domain；Another kind is recognized Slowly varying for deviation, in detection spatial domain nonuniform Distribution.More realistic is that latter is false If systematic error is the multivariable function with the change of detection spatial domain, by partially to have researcher to assume Difference estimated value utilizes least square fitting to go out function coefficients.This method needs substantial amounts of number According to, and, matching order and Variable selection are all suitable stubborn problems.
Summary of the invention
The defect existed with compensation technique for existing sensing system error estimation, the present invention carries Go out a kind of airborne sensor systematic error estimation based on cooperative target and compensation method, the present invention The observation data configuration to it first with cooperative target self poisoning information and airborne sensor Systematic error equation；Then use equivalent method, use autoadaptive filtering technique to estimate measurement System deviation and determine the systematic error that appearance deviation is superimposed；Finally according to search coverage to non Cooperative target metric data carries out partition compensation.
The goal of the invention of the present invention is achieved through the following technical solutions:
The first step, by distinguishing inspection cooperative target and noncooperative target data；Specific practice is
It is divided into N number of region, each region to set two and deposit sensor space exploration by rule Storage area: cooperative target district and noncooperative target district.According to target metric data and target whether It is that cooperative target stores data into respective regions.
Second step, utilizes the location data of cooperative target and sensor to its metric data instrument error side Journey；Specific practice is
(1) cooperative target location data are transformed into ECEF coordinate by geodetic coordinates
The geodetic coordinates of target location is (L, λ, H), and wherein, L represents latitude, and λ is longitude, H is height, then its corresponding ECEF coordinate (x_{e},y_{e},z_{e}) it is
Wherein
E_{q}Being equatorial radius, e is eccentricity of the earth.
(2) by ECEF Coordinate Conversion to local rectangular coordinates
Local rectangular coordinate system usually approximates inertial coodinate system.ECEF coordinate is to partial, right angle The conversion of coordinate is typically through rotating and two links of translation, and wherein spin matrix is generally according to seat Parameter to definition and direction cosines solve.
Target is [x at ECEF coordinate_{e},y_{e},z_{e}]^{T}, carrier aircraft ECEF coordinate now is [x_{eo},y_{eo},z_{eo}]^{T}, it is C that ECEF coordinate is tied to local rectangular coordinate system spin matrix_{1}, then mesh The coordinate being marked on local rectangular coordinate system is
(3) it is transformed into sensor measurement coordinate by local rectangular coordinates
Sensor measurement coordinate system is typically a kind of nonstable coordinate system, and it is sat with partial, right angle Conversion between mark system generally need to use the attitude angle information of sensor (when being rigidly connected, also referred to as For platform stance angle, for yaw angle α, pitching angle beta, roll angle γ).
The local rectangular coordinates of target is [x_{g},y_{g},z_{g}]^{T}, local rectangular coordinate system is to sensor The spin matrix measuring coordinate system (rectangular system) is C_{2}(C_{2}Value is determined by platform stance angle), Then target at the coordinate of sensor measurement coordinate system (rectangular system) is
Target is at the coordinate distance ρ of sensor measurement coordinate system (ball system)^{d}, azimuth Pitching angle theta^{d}, for
(4) cooperative target measurement information instrument error equation is combined
Sensor is distance ρ to the metric data of target^{m}=ρ '+Δ ρ+v_{ρ}(t), orientation AnglePitching angle theta^{m}=θ '+Δ θ+v_{θ}(t)；Wherein, Respectively measure true value,For Measurement Biases,For random error. Platform stance angle α=α '+Δ α, β=β '+Δ beta, gamma=γ '+Δ γ, α ', β ', γ ' is respectively corresponding true value, Δ α, Δ β, Δ γ is for determine appearance deviation.Error between target metric data and object location data is Δ α, Δ β, Δ γ,Function, then error equation is represented by
Wherein,
3rd step, analysis deviation source, select suitable bias vector, linearized stability equation；Specifically Way is
(1) deviation variables is selected
ξ^{m}ξ^{d}Being the function about six deviation variables, traditional way is through complicated Derivation is tried to achieveAnalytic expression, then f () is carried out one Rank Taylor expansion can obtain the approximately linear expression formula of f ().It will be clear that now need to estimate Parameter more, only with ξ^{m}ξ^{d}Threedimensional information is difficult to ensure that the observability of system.Therefore, Select hereinIt is added to as Δ α, Δ β, Δ γAfter on Equivalence Measurement Biases as system deviation vector.
(2) linearisation
Select equivalence Measurement BiasesAs system deviation, then linearisation just becomes non The simplest, for
Wherein,
4th step, affects the different occasions of filtering performance according to noise characteristic, improves adaptivefiltering skill Art presses subregion estimated bias parameter；Specific practice is
(1) structural regime equation and measurement equation
OrderAssume that equivalent deviation is slowly varying, then state equation is
X_{k+1}=X_{k}+w_{k},
Measurement equation is
Z=HX_{k+1}+v_{k},
(2) filtering initializes
Estimate initial valueInitial estimation error battle arrayMeasurement noise initial variance
Battle arrayProcess noise initial variance battle arrayAdaptivefiltering attenuation quotient
(3) time updates and processnoise variance battle array ART network
Onestep prediction:
Predicting covariance battle array:
Measuring noise square difference battle array ART network
(4) renewal and processnoise variance battle array ART network are measured
Filtering gain battle array:
Estimation updated value:
Estimation difference covariance matrix:
P_{kk}=(IK_{k}H_{k})P_{kk1},
Processnoise variance battle array ART network:
5th step, carries out partition compensation to noncooperative target metric data, obtains the amount after deviation compensation Survey data；Specific practice is
(1) subregion belonging to noncooperative target is defined
The principle that subregion belonging to noncooperative target defines is that the target information detected according to sensor is Regionalization basis.During compensation, each bat all needs to calculate.
(2) compensation is measured
Noncooperative target measuresThe nth etc. of subregion belonging to this target Effect estimation of deviation result isMetric data after then compensating is
Measurement used by subsequent treatment (such as filtering) just usesζ ^{m}.It addition, when target is from one point When district enters another subregion, the corresponding equivalent deviation compensated also to change therewith.
Compared with prior art, the present invention first avoids multiple error parametric variable and estimates simultaneously Time the most considerable problem of system；Second, solve system by mistake by introducing autoadaptive filtering technique Slowly varying and other unknown noises of difference exist in the case of estimation problem；3rd, to nonconjunction Making target measurement takes partition compensation to compensate residual error with further reduction according to region.Experiment proves Strong robustness of the present invention, reliability are high, computation complexity is low, are particularly wellsuited to engineering practice.
Accompanying drawing explanation
Fig. 1 is fundamental diagram of the present invention
Fig. 2 is the 1st subregion equivalent distances estimation of deviation result
Fig. 3 is the 1st subregion equivalence azimuth deviation estimated result
Fig. 4 is the 1st subregion equivalence pitch deviation estimated result
Fig. 5 is noncooperative target distance measuring deviation compensation whether results contrast
Fig. 6 is noncooperative target azimuthal measuring deviation compensation whether results contrast
Fig. 7 is whether noncooperative target pitching Measurement Biases compensates results contrast
Fig. 8 be noncooperative target measure whether compensate filter after RMS compare
Detailed description of the invention
The invention will be further described below in conjunction with the accompanying drawings: the present embodiment is with the technology of the present invention Implement under premised on scheme, give detailed embodiment and concrete operating process, But protection scope of the present invention is not limited to following embodiment.
This section illustrates for embodiment with onboard radar system error estimation with compensating, the present embodiment bag Include following steps:
The first step, by distinguishing inspection cooperative target and noncooperative target data；It is specially
It is divided into N number of region, each region to set two sensor space exploration by certain rule Individual memory block: cooperative target district and noncooperative target district.According to target metric data and target Whether it is that cooperative target stores data into respective regions.
Second step, utilizes the location data of cooperative target and sensor to its metric data instrument error side Journey；Concretely comprise the following steps
Local rectangular coordinate system (carrier aircraft geographic coordinate system) selects sky, northeast system.Sensor measurement Coordinate system is consistent with carrier aircraft coordinate system is spherical coordinate system, and carrier aircraft coordinate system is former with carrier aircraft barycenter Point, xaxis along carrier transverse axis to the right, yaxis along before carrier Ydirection, zaxis along carrier vertical pivot to On.
(1) cooperative target location data are transformed into ECEF coordinate by geodetic coordinates
The geodetic coordinates of target location is (L, λ, H), and wherein, L represents latitude, and λ is longitude, H is height, then its corresponding ECEF coordinate (x_{e},y_{e},z_{e}) it is
Wherein
E_{q}Being equatorial radius, e is eccentricity of the earth.
(2) by ECEF Coordinate Conversion to carrier aircraft geographical coordinate
ECEF coordinate system is transformed into the spin matrix of carrier aircraft geographic coordinate system (sky, northeast system) (λ, L are respectively carrier aircraft place longitude, latitude)
Target is [x at ECEF coordinate_{e},y_{e},z_{e}]^{T}, carrier aircraft ECEF coordinate now is [x_{eo},y_{eo},z_{eo}]^{T}, it is C that ECEF coordinate is tied to carrier aircraft geographic coordinate system spin matrix_{1}, then target Coordinate in carrier aircraft geographic coordinate system is
(3) it is transformed into carrier aircraft coordinate by carrier aircraft geographical coordinate
Carrier aircraft geographical coordinate is tied to the spin matrix of carrier aircraft coordinate system for (α, β, γ are respectively carrier aircraft Yaw angle, the angle of pitch, roll angle)
The carrier aircraft geographical coordinate of target is [x_{g},y_{g},z_{g}]^{T}, then target is at carrier aircraft coordinate system (right angle System) coordinate be
It is transformed under carrier aircraft spherical coordinate system, then distance ρ^{d}, azimuthPitching angle theta^{d}It is respectively
(4) instrument error equation
Wherein,Represent respectively target metric data and Data under the measurement coordinate system come by targeting information conversion； Δ θ is respectively needs (platform) yaw angle deviation of estimation, (platform) pitch angle deviation, horizontal stroke Roll angle deviation, (target) measure range deviation, (target) measures azimuth deviation, (aim parameter Survey) pitch deviation.
3rd step, analysis deviation source, select suitable bias vector, linearized stability equation；Specifically Step is
SelectEstimate as equivalent distance, orientation, pitch deviation, linearisation Error equation be
4th step, autoadaptive filtering technique based on a kind of improvement presses subregion estimated bias parameter；Specifically Step is
Use adaptive filter algorithm to carry out estimation of deviation, state equation and measurement equation to be respectively
X_{k+1}=X_{k}+w_{k},
Z=HX_{k+1}+v_{k},
Estimate initial valueInitial estimation error battle arrayMeasure Noise initial variance battle arrayProcess noise initial variance battle arrayAdaptivefiltering declines Subtract coefficientWherein λ=0.2.Then estimation of deviation based on adaptivefiltering is pressed Equation below is carried out.
5th step, carries out partition compensation to noncooperative target metric data, obtains the amount after deviation compensation Survey data；Concretely comprise the following steps
First subregion belonging to current bat time noncooperative target measurement is calculated, then from straggling parameter storehouse The corresponding parameter value of middle extraction compensates.Noncooperative target measures The nth equivalent deviation estimated result of this target now affiliated subregion isAmount after then compensating Survey data are
Measurement used by subsequent treatment (such as filtering) just usesζ ^{m}。
Test case
Arrange radar measurement distance random error standard deviation be 100 meters, system of distance deviation be + 30 meters, radar measurement orientation random error standard deviation is 0.5 degree, azimuth system deviation is+1 Degree, radar measurement pitching random error standard deviation is 0.5 degree, pitch system deviation is+0.5 degree. Carrier aircraft platform navigation is determined appearance deviation (yaw angle, the angle of pitch, roll angle) and is+0.1 degree. Cooperative target (quantity is some) be evenly distributed in sensor detection areas, noncooperative target (number Measure 1) with the distance of carrier aircraft at 80 km.8 districts are divided in sensor detection areas.
Fig. 2 to Fig. 4 is the 1st subregion equivalent distances deviation, equivalence azimuth deviation and equivalence respectively Pitch deviation estimated result.It is found that because the existence of carrier aircraft platform navigation attitude angle deviation, One is had between equivalent deviation (orientation, pitching) and radar measurement deviation (azimuth pitch) The difference of relative constancy.Other subregions can be similar to experimental result.
Fig. 5 to Fig. 7 be respectively noncooperative target after systematic error partition compensation with compensate before Metric data contrast.Because the existence of systematic error, the metric data before compensation and true value it Between there is the droop of relative constancy；And after partition compensation, this relativelystationary partially Difference reduces (contrast on pitch channel is especially apparent).
Fig. 8 is that noncooperative target measures the contrast whether compensating filter result, and both difference are The most obvious.This is because target metric data is not only polluted by sensor Measurement Biases Also receive the pollution of navigation attitude misalignment, if both impacts, target can not be effectively eliminated Following the tracks of result will be the most undesirable.The present invention can successfully solve two kinds of simultaneous feelings of deviation Condition, therefore after metric data is compensated, tracking performance is greatly improved.
It is above the present invention preferably embodiment, but those skilled in the art should manage Solving, these are merely illustrative of, on the premise of without departing substantially from the principle of the present invention and essence, and can So that these embodiments are made various changes or modifications.Therefore, protection scope of the present invention by Appended claims limits.
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